Joseph R. Bourne
Papers
10
Total Citations
384
H-Index
7
About
Joseph R. Bourne is a robotics and autonomous systems researcher whose work spans mobile robot navigation, chemical plume detection, and multi-agent coordination. He has made significant contributions to collision avoidance methodologies, most notably through his highly cited 2021 comparative analysis of Control Barrier Functions and Artificial Potential Fields (149 citations), which has become an important reference for researchers designing safe robot motion planning systems. His work on autonomous chemical-sensing robots demonstrates a strong commitment to real-world applications, including environmental monitoring and hazardous gas leak localization. Bourne has developed innovative Bayesian-based and information-theoretic algorithms for plume source estimation and target localization, with his 2019 bioinspired plume-seeking work earning 77 citations and his decentralized multi-agent control framework attracting 41. His research extends to aerial robotics, producing practical collision avoidance systems for unmanned aerial vehicles navigating complex outdoor environments. Notably, his humanitarian applications—such as Bayesian estimation for locating avalanche victims—highlight the breadth of his impact. Collectively, Bourne's portfolio reflects a researcher who bridges rigorous theoretical development with compelling, life-saving practical deployment.
Research Focus
Key Achievements
Top Papers
- 1
- 2
- 3
- 4
- 5
- 6
- 7Gaussian-Based Kernel for Multi-Agent Aerial Chemical-Plume Mapping14 citations · 2019
- 8
- 9
- 10